With increased computing power

electronic storage capacity

and the rapid development of the Internet

the potential for large digital image libraries is now growing at an astonishing pace. Providing efficient access to images

however

is not an easy task. To overcome this difficulty

content-based image retrieval(CBIR) was thus proposed as a solution. In CBIR

images would be indexed by their own visual content

instead of being manually annotated by text-based keyword s. In this framework

many research studies have been performed

and many commercial and academic CBIR systems

widely applied in multimedia databases

digital libraries

medical image management

public security department and satellite image management

have been developed in the past few years. Most CBIR systems

however

answer users' query by similarity match based on multi-dimensional physical image features. Because of human subjectivity

different persons or the same person under different circumstances may perceive the same visual content differently. To address the difficulties arising from human subjectivity

we propose a content-based interactive emotional image retrieval approach. Through interactive evolution computation

human intuition and emotion is integrated into the evolution process to realize on-line retrieval by human-computer interaction. To deal with the problem that the user may tend to be tired arising from that the user has to evaluate a large number of individuals when the evolution time is too long

neural networks are used for off-line learning to alleviate human fatigue. Based on image content

an emotional image retrieval system has been realized. The experimental results demonstrate the effectiveness of our approach.